Welcome to .txtLAB, a laboratory for cultural analytics at McGill University directed by Andrew Piper. We explore the use of computational and quantitative approaches towards understanding literature and culture in both the past and present. Our aim is to engage in critical and creative uses of the tools of network science, machine learning, or image processing to think about language, literature, and culture at both large and small scale.

The .txtLAB Guide on How to Write Like a Bestseller

Here is a humble 1-page guideline that we produced after studying a sample of 10 years worth of the bestselling novels according to the NY Times Bestseller list. It was used as part of the Devoir Challenge in which some local Montreal writers were asked to try to write stories “like an American bestseller.”

One of the most interesting things we found when we sampled this past year’s bestsellers was that nothing much seems to have changed. In fact, the only really strong difference we detected was more emphasis on technology (more texting, phones, email, laptops, photographs, screens, and video). At the same time, there was less bitterness, genuineness, learning, and faith, and sadly more murders, police, lawyers and detection.

One question we were left with is just how stable this vocabulary is over time. Do bestsellers really reflect their times, and if so, what is the relevant time-frame (a year, a decade, a generation)? Or maybe they just consist of a relatively consistent set of tropes (action, police procedures, etc) recycled into a variety of insignificant sub-plots. More work to be done there.

How to write like a Bestseller

***Things to focus on:

Try to use many more characters than normal (about 30% more per novel).

Try to use more dialogue, about 50% more than you would normally.

Try to focus more on people, pronouns and actions:

More than 50% of the unique grammatical patterns in Bestsellers involve proper names

This is another popular formulation: gerund – to – verb, as in “going to run”